Filterbank structure and method for filtering and separating an information signal into different bands, particularly for audio signal in hearing aids

ABSTRACT

A filterbank structure is provided which provides a flexible compromise between the conflicting goals of processing delay, filter sharpness, memory usage and band interaction. The filterbank has an adjustable number of bands and a stacking which provides for a selectable shift of band frequencies to one of two discrete sets of center frequencies. The width of the bands and hence the number of the bands is selected depending upon acceptable delay, memory usage, and processing speed required. The flexibility in terms of stacking of the bands provides twice the number of potential band edge placements, which is advantageous for hearing loss fitting, especially at low frequencies. The same filter coefficients can be used for analysis and synthesis, to reduce memory usage.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims benefit from U.S. provisional application serialNo. 60/041,977 filed on Apr. 16, 1997.

FIELD OF THE INVENTION

This invention relates to a filterbank structure and a method forfiltering and separating an information signal into different bands,particularly for such filtering and separation of audio signals inhearing aids. This invention more particularly relates to such atechnique carried out using digital signal processing in hearing aids.This invention more particularly relates to a method and architecturefor a digital filterbank for hearing aid applications.

BACKGROUND OF THE INVENTION

Hearing loss is generally associated with a loss of hearing sensitivitywhich is a function of frequency. The most common type of sensitivityloss is an increasing function of frequency. Sensitivity is typically afunction of speech level as well. Hence, loud sounds should be amplifiedless than soft sounds. It has been long known that a hearing aid shouldtreat the various frequency components of speech differently to renderthem intelligible to a hearing impaired person.

Known analog hearing aids use relatively simple methods to alter theirfrequency shaping and dynamic range compression to mitigate the loss inhearing sensitivity for frequency and level.

SUMMARY OF THE INVENTION

Digital techniques promise far greater possibilities for signalprocessing to aid the hearing impaired. The present inventors havecombined processing. This allows great processing flexibility as thebands can be treated independently to compensate more precisely forhearing loss.

In accordance with the first aspect of the present invention, there isprovided an oversampled filterbank for filtering an information signal,the filterbank having a filterbank structure comprising a filter meansdefining a filter bandwidth, said filter means filtering saidinformation signal and separating said information signal into aplurality of frequency band signals each representing one of a pluralityof uniformly spaced frequency bands within said filter bandwidth, saidfrequency bands being stacked in one of an even and an odd manner andsaid frequency bands overlapping, such that the summation of theunmodified frequency hand responses of the plurality of said frequencybands sums to a function within a predetermined passband ripple oversaid filter bandwidth, wherein the filter means includes a selectioninput enabling at least one of the following to be selected:

(i) the number of frequency band signals,

(ii) the bandwidth of said frequency bands,

(iii) selection of stacking of said frequency bands in one of an evenand an odd manner,

(iv) the degree of overlap between said frequency bands,

(v) an oversampling factor by which said frequency band signals aresampled above the theoretical minimum of critical sampling.

It is to be appreciated that while it is envisaged that the number offrequency bands and their bandwidth will usually be parameters that canbe adjustable by the selection input, this is not always the case. Moregenerally, the filterbank can be configured to enable one or more ofusual parameters of a digital filterbank to be adjustable, and these caninclude: the number of bands; the width of each band; whether the bandshave abutting band edges, overlap or are spaced apart; coefficients forboth analysis and synthesis windows; whether there is any relationshipbetween the analysis and synthesis windows; even or a odd stacking ofbands; and the degree of oversampling above the critical sampling rate.Details of these parameters are set our below.

Preferably, the selection input enables at least one of the number offrequency bands and selection of stacking of said frequency bands in oneof an even and an oddmanner to be selected, said number of frequencybands being equal to N, and the filter means comprises: (a) a firstanalysis filterbank means for separating said signal into the pluralityof N separate frequency band signals; (b) processing means for receivingand processing each of said separate frequency band signals to provide Nseparate processed frequency band signals; and (c) a second synthesisfilterbank means for receiving and recombining the N separate processedfrequency band signals into a single output signal, wherein both of thefirst analysis filterbank means and the second synthesis filterbankmeans are connected to the selection input, the processing means beingcoupled between the first analysis filterbank means and the secondsynthesis filterbank means.

In another aspect of the present invention, the filterbank comprises adedicated application specific integrated circuit (ASIC), said ASICincluding the first analysis and the second synthesis filterbanks, and aprogrammable digital signal processor for controlling the number offrequency bands and the bandwidth of each frequency band, said digitalsignal processor being provided with the selection input.

The filterbank may be adapted to receive a single real monauralinformation signal, wherein said transform means generates non-negativefrequency band signals and negative frequency band signals, saidnegative frequency band signals being derivable from the non-negativefrequency band signals, and said processing means processes only saidnon-negative frequency band signals. Alternatively is adapted to filteran audio signal comprising first and second real monaural informationsignals which are combined into a complex stereo signal and wherein saidtransform means generates N combined frequency band signals, and whereinsaid processing means includes: (a) channel separation means forseparating the N combined frequency band signals into the N frequencyband signals corresponding to said first information signal and the Nfrequency band signals corresponding to said second information signal,each of said N frequency band signals comprising non-negative andnegative frequency band signals; (b) first independent channelprocessing means connected to the channel separation means for receivingand processing each of said separate frequency band signals of saidfirst information signal to provide a first set of N separate processedfrequency band signals; (c) second independent channel processing meansconnected to channel separation means for receiving and processing eachof said separate frequency band signals of said second informationsignal to provide a second set of N separate processed frequency bandsignals; and (d) channel combination means connected to the first andsecond independent channel processing means for combining said first setof N processed separate frequency band signals and said second set of Nprocessed separate frequency band signals.

In accordance with another aspect of the present invention, there isprovided a method of processing an information signal to selectivelymodify different frequency bands, the method comprising the steps of:(1) defining a filter frequency bandwidth to be analyzed; (2) dividingthe filter frequency bandwidth into a plurality of uniformly spacedbands, said frequency bands being stacked in an even or odd manner andsaid frequency bands abutting, overlapping, or being spaced apart fromone another; (3) filtering the information signal to separate the signalinto a plurality of frequency band signals, each representing one ofsaid uniform filter bands; (4) processing the frequency band signals;(5) recombining the signals of the individual bands to form an outputsignal; and (6) providing an input for enabling at least one of thefollowing to be selected: (i) the number of frequency band signals, (ii)the bandwidth of said frequency bands, (iii) whether said frequencybands are stacked in an even or odd manner, (iv) whether said frequencybands abut, overlap, or are spaced apart from one another, and (v) adecimation factor by which said frequency band signals are downsampled.

In another aspect the method includes transforming the informationsignal into the frequency domain, providing N separate frequency bandsignals in the frequency domain, and effecting an inverse transform ofthe N separate processed frequency band signals into the output signalin the time domain.

The signal, in one variant of the invention, is filtered to give aplurality of evenly stacked bands, as described in Crochiere, R. E. andRabiner, L. R., Multirate Digital Signal Processing, (Prentice-Hall,1988) which is incorporated herein by reference. Alternatively, it canbe filtered to give a plurality of oddly stacked bands. This has theadvantage that the placement of the band edges is selectable and thistechnique gives twice the number of potential band edges. The band edgescan be selected depending on the characteristics of a person's hearingloss. In further variants of the invention, other parameters of adigital filterbank are made adjustable either alone or in combination.

DESCRIPTION OF THE DRAWING FIGURES

For a better understanding of the present invention and to show moreclearly how it may be carried into effect, reference will now be made,by way of example, to the accompanying drawings, which show a preferredembodiment of the present invention, and in which:

FIG. 1 shows schematically a block diagram of an ASIC data pathprocessor and a programmable DSP unit in accordance with the presentinvention;

FIGS. 2a and 2 b show schematically stacking arrangements for even andodd uniform filterbanks;

FIGS. 2c and 2 d show simulated stacking arrangements for even and odduniform filterbanks showing typical filter characteristics;

FIGS. 3 and 3a show details of the filterbank analysis structure formonaural and stereo processing,

FIG. 4 shows details of the filterbank synthesis structure.

DESCRIPTION OF THE PREFERRED EMBODIMENT

With reference to the drawings, the apparatus of the present inventionhas a microphone 10, as a first input, connected to a preamplifier 12,which in turn is connected to an analog-to-digital (A/D) converter 14.In known manner this enables an acoustic, audio-band signal, forexample, to be received in the microphone, preamplified and converted toa digital representation in the A/D converter 14. A secondary input 11(which may also comprise a microphone) may also be connected to apreamplifier 13 which is in turn connected to an analog-to-digital (A/D)converter 15. While FIG. 1 shows an audio input signal or signals, thepresent invention is not limited to use with such signals and can haveother information signals, such as a seismological signal, as an input.In the present invention, the term monaural describes embodiments whichprocess one digital stream and the term stereo describes embodimentswhich process two digital streams. Theoretically, according to theNyquist Sampling Theorem, provided a signal is sampled at a rate of atleast twice the input signal bandwidth, there will be adequateinformation content to reconstruct the signal. This minimum samplingrate required for reconstruction is commonly referred to as the Nyquistrate.

The output of the A/D converter 14 (and where a secondary input exists,the output of A/D converter 15) is connected to a filterbank applicationspecific integrated circuit (ASIC) 16 as shown in FIG. 1 or,alternatively, directly to a programable DSP unit 18 via a synchronousserial port. Additional A/D converters (not shown) may be provided topermit digital processing of multiple separate input signals. Furtherinput signals may be mixed together in the analog domain prior todigitization by these A/D converters. Mixing may also be done in thedigital domain using the programmable DSP prior to processing by amonaural filterbank. The output of the filterbank ASIC 16 is connectedto a digital-to-analog (D/A) converter 20. The converter 20 is in turnconnected through a power amplifier 22 to a hearing aid receiver 24.Thus, the filtered signal, in known manner, is converted back to ananalog signal, amplified and applied to the receiver 24.

The output of the A/D converter 14, and any additional A/D converterthat is provided, may, instead of being connected to the ASIC 16 asshown, be connected to the programmable DSP 18 via a synchronous serialport. Similarly, the output D/A converter 20 can alternatively beconnected to the programmable DSP 18.

Within the filterbank ASIC 16, there is an analysis filterbank 26, thatsplits or divides the digital representation of the input signal orsignals into a plurality of separate complex bands 1-N. As shown in FIG.1, each of these bands is multiplied by a desired gain in a respectivemultiplier 28. In the case of monaural processing, the negativefrequency bands are complex conjugate versions of the positive frequencybands. As a result, the negative frequency bands are implicitly knownand need not be processed. The outputs of the multipliers 28 are thenconnected to inputs of a synthesis filterbank 30 in which these outputsare recombined to form a complete digital representation of the signal.

For stereo processing, the complex conjugate symmetry property does nothold. In this case, the N band outputs are unique and represent thefrequency content of two real signals. As indicated below and shown inFIG. 3a, the band outputs must first be processed to separate thecontent of the two signals from each other into two frequency domainsignals before the gain multiplication step is performed. The twofrequency separated signals are complex conjugate symmetric and obey thesame redundancy properties as described previously for monauralprocessing. Multiplier resource 28 must, therefore, perform two sets ofgain multiplications for the non-redundant (i.e. positive frequency)portion of each signal. After multiplication, the signals are combinedinto a monaural signal, and further processing is identical to themonaural case.

In known manner, to reduce the data and processing requirements, theband outputs from the analysis filterbank 26 are down-sampled ordecimated. Theoretically, it is possible to preserve the signalinformation content with a decimation factor as high as N, correspondingto critical sampling at the Nyquist rate. This stems from the fact thatthe bandwidth of the N individual band outputs from the analysisfilterbank 26 is reduced by N times relative to the input signal.However, it was found that maximum decimation, although casingcomputational requirements, created severe aliasing distortion ifadjacent band gains differ greatly. Since this distortion unacceptablycorrupts the input signal, a lesser amount of decimation was used. In apreferred embodiment, the band outputs are oversampled by a factor OStimes the theoretical minimum sampling rate. The factor OS represents acompromise or trade-off, with larger values providing less distortion atthe expense of greater computation (and hence power consumption).Preferably, the factor OS is made a programmable parameter by the DSP.

To reduce computation, a time folding structure is used as is shown inthe transform-based filter bank of FIG. 3, and described in greaterdetail below. After applying a window function, which is also referredto as a prototype low pass filter, to the incoming signal, the resultingsignal is broken into segments, stacked and added together into a newsignal. This signal is real for monaural applications and complex forstereo applications. The output of the analysis filterbank is the (evenor odd) discrete Fourier transform (DFT) of this segment signal (the DFTis normally implemented with a fast Fourier transform algorithm). Forstereo applications a complex DFT must be used, whereas for monauralapplications a real input DFT may be used for increased efficiency. Aswill be known to those skilled in art, the odd DFT is an extension ofthe even or regular DFT as described in Bellanger, M., DigitalProcessing of Signals, (John Wiley and Sons, 1984), which isincorporated herein by reference. Thus in the preferred embodiment, thepresent invention comprises a transform-based filterbank in which theaction of the DFT is as a modulator or replicator of the frequencyresponse of the prototype low pass filter (i.e. the window function), sothat the discrete Fourier transform of the windowed time domain signalor signals results in a series of uniformly spaced frequency bands whichare output from the analysis filterbank. The time-folding structure ofthe present invention further allows the number of frequency bands andtheir width to be programmable. In doing so, this time-folding structurereduces the size of the DFT from the window size to the segment size andreduces complexity when the desired number of filter bands is less thanthe window size. This technique is shown generally for a filterbank ofwindow size L and DFT size N in FIG. 3. In total there are N fullfrequency bands including both non-negative and negative frequencybands, represented by N frequency band signals. For monauralapplications these bands (i.e. the band signals) may be processeddirectly. In stereo applications, the frequency content of the two inputsignal streams are first separated as shown in FIG. 3a. As previouslyindicated, in the monaural case, the negative frequency bands areredundant because they can be exactly derived from the positivefrequency bands (since they are complex conjugate versions of eachother). As will be obvious to one skilled in the art, the positivefrequency bands, i.e. the positive frequency band signals, couldalternatively be derivable from the non-positive frequency bands, i.e.the non-positive frequency band signals. Effectively, therefore, thereare N/2 non-negative complex frequency bands of normalized width 2π/Nfor odd stacking; and there are N/2-1 non-negative complex frequencybands of width 2π/N and 2 non-negative real frequency bands of width π/Nfor even stacking. This is illustrated in FIG. 2a for N=8.

As shown in FIG. 2a (the output of each filterbank channel is bandlimited to 2π/N and each band output can be decimated by the factor R(i.e. its sampling rate is reduced by keeping only every Rth sample)without, theoretically, any loss of fidelity if R≦N. As mentionedearlier, it is not possible to maximally decimate this filterbank (i.e.to have the input sample shift R equal the DFT size N) and obtain usefulresults when extensive manipulation of the frequency content is requiredas in hearing aids. Accordingly, the decimation factor, which is N forcritical sampling, is less by a factor of OS. This is accomplished byshifting the input samples by R=N/OS rather than by N. This isadvantageous in reducing the group delay since the processing latency(i.e. the delay created by the FIFO) shifting) is smaller by the factorOS. The increase in the band sampling rate eases the aliasingrequirements on the analysis filter. Additionally, spectral images arepushed further apart reducing the image rejection requirements on thesynthesis filter. Lowering the requirements of these filters furtherreduces delay (since these filters can be simpler, i.e. of lower order).While maximum oversampling, i.e. OS=N, provides for optimalreconstruction of the input signal or signals, this results generally inunacceptable computational expense.

With reference to FIG. 3, the overlap-add analysis filterbank 26includes an input 50 for R samples. In known manner, the exact size orword length of each sample will depend upon the accuracy required,whether it is fixed-point or floating-point implementation etc. Theinput 50 is connected to a multiplication unit 52 which also has aninput connected to a circular ± sign sequencer input 54 having a lengthof 2*OS samples. This circular sequencer input 54, which may begenerated by a shift register, has a series of inputs for odd stackingof the filter bands and inputs for even stacking of the filter bands.

In the multiplication unit 52, for the even filterbank structure, eachblock of R input samples is multiplied by +1, so as to remain unchanged.For the even DFT, which has basis functions ending in the same sign(i.e. which are continuous), no modulation is required to obtaincontinuous basis functions.

For the odd filterbank structure, the first OS blocks of R input samplesare multiplied by +1 and the next OS blocks by −1, the next OS blocks by+1, etc. Since the odd DFT has basis functions ending in opposite signs(i.e. which are not continuous), this modulation serves to producecontinuous basis functions.

The output of the multiplication unit 52 is connected to a first buffer56 holding L samples, indicated as X(1:L). These samples are split upinto individual segments 57, each of which contain R samples. The buffer56 is sized so that the L samples form a desired window length. Thelarger the window length L, the more selective each channel becomes atthe expense of additional delay. The buffer 56 is connected to a secondmultiplication unit 58, together with a window function 60, indicated asW(1:L). The modulation property of the fast Fourier transform procedurecreates a complete uniformly spaced filterbank by replicating thefrequency response of the window function (also referred to as theprototype low-pass filter) at equally spaced frequency intervals. It isnecessary to properly design this window function to give a desiredpassband and stopband response to the filter bands and thereby reduceaudible aliasing distortion.

The window function (which is a prototype low pass filter) ideallysatisfies the requirements for a good M-band filter, i.e. a good lowpass filter which has zeros at every interval of N samples. Other windowfunctions can also be used. See Vaidyanathan, P. P., “Multirate DigitalFilters, Filter Banks, Polyphase Networks, and Applications: ATutorial”, Proc. IEEE, Vol. 78, No. 1, pp. 56-93 (January 1990), whichis incorporated herein by this reference. As will be appreciated bythose skilled in the art, this filter may be designed as a windowed sincfunction or by using Eigenfilters (see Vaidyanathan, P. P., and Nguyen,T. Q., “Eigenfilters: A New approach to least-squares FIR filter designand applications including Nyquist filters”, IEEE Trans. on Circuits andSystems, Vol. 40, No, 4 (December 1994), pp. 11-23). The coefficients ofthe window function are generated by the programmable DSP or generatedand stored in non-volatile memory. A general window is typically storedin non-volatile memory, however for the parametric classes of windowsbased on the sinc function, the window function need not be stored as itmay be calculated on system initialization using only a few parameters.

The output of the second multiplication unit 58 is connected to a secondoutput buffer 62. This output buffer 62 again has the same L samples,arranged into segments 64. Here, the segments contain N samples. In atypical embodiment, N might equal 32 and the number of channels is 16(for an odd DFT/odd stacking) or 17 (for an even DFT/evenstacking—because of the two half bands). For adequate selectivity withband aliasing reduction greater than 55 dB, a window length L of 256sampling can be used (the window length L is constrained to be amultiple of N, and in preferred embodiments is also a multiple of 2^(N)for computational simplicity) and the over-sampling factor, OS, shouldbe 2 or greater. For example, letting OS equal 2 results in R equal to16 (i.e. N/OS). As mentioned earlier, for monaural applications, thesamples are real, and for stereo applications the samples are complex.

The segments are separated, and as indicated below the buffer 62,individual segments 64 are added to one another to effect the timefolding or time aliasing operation, and thereby reduce the number ofnecessary computations in processing the input signal or signals. Thedetails of the time folding step are described in Crochiere, R. E. andRabiner, L. R., Multirate Digital Signal Processing, supra. Ideally, thetime folding step does not result in any loss of information, and inpractical implementations any resulting loss can be made insignificant.The addition is performed, and the result is supplied to circular shiftsequencer 66, which is preferably a circular shift register, as shown inFIG. 3. This shift register 66 holds N samples and shifts the samples byR samples (where R=N/OS) at a time.

The time aliased stacked and summed total is then subject to an odd FFT,or even FFT as required, by the FFT unit 68 (as shown in FIG. 3 formonaural applications) or the FFT unit 68′ (as shown in FIG. 3a forstereo applications) to produce the DFT. The DFT provided by 68 is anN-point transform with real inputs (monaural), and the DFT provided by68′ is an N-point transform with complex inputs (stereo). For monauralapplications, the non-negative frequency components of the DFT output bythe FFT unit 68, and a set of gain values G(1:N/2) for odd stacking (orG(1:N/2+1) for even stacking) from a multiplier resource unit 70, areconnected to a multiplication unit 72. This gives an output 74 ofU(1:N/2) for odd stacking (or U(1:N/2+1) for even stacking) which iscomplex, i.e. with a magnitude and phase, in known manner.

As illustrated in FIG. 3a, for stereo applications the two channels mustfirst, i.e. before the multiplication step, be separated in a stereochannel separation step indicated at 76. To illustrate, consider thecase of two real time domain signals x1 and x2 which have been combinedinto a single complex signal x1+jx2, where x1 and x2 are sample vectorswhich are N frequency domain samples long. Since the filterbankoperation is linear, the resulting output from the analysis filterbankis X1+jX2, where X1 and X2 are also N samples long. The frequencyinformation of the two channels X1 and X2 are separable by using thesymmetry relationships present in the N band outputs (i.e. the firstchannel spectrum has a symmetric real portion and an anti-symmetricimaginary portion, whereas the second channel has an anti-symmetric realportion and a symmetric imaginary portion). As a result, well knownoperations are all that are necessary to separate the two channels: seeB. P. Flannery, S. A. Teukolsky, W. T. Vetterling, Numerical Recipes inC, (Cambridge University Press: 1991) Chapter 12.

After separation, the non-negative frequency components of these datastreams are each multiplied by a separate set of gain values frommultiplier resources 70A and 70B respectively (multiplier resources 70Aand 70B typically represent the separate processing of the left andright channels, and each contains N/2 values for odd stacking or N/2+1values for even stacking). After the multiplication steps at 72A and72B, the two channels are combined in a combine channels step indicatedat 78, which provides an output 74 as in the monaural case. Thecombination step 78 is simply the point by point summation of the twofrequency domain streams.

As compared to FIG. 1, the multiplication units 72 of FIG. 3 and 72A and72B of FIG. 3a are equivalent to the multiplication units 28 shown inFIG. 1.

Reference will now be made to FIG. 4, which shows the correspondingsynthesis filterbank. Here, the input is shown at 80 of the complexrepresentation of the signal in the frequency domain, U(1:N/2) for oddstacking (or U(1:N/2+1) for even stacking). This is converted to thetime domain by an inverse DFT, which again is odd or even as requiredand which is implemented by the inverse PFT (IFFT) algorithm unit 82. Inknown manner, the IFFT unit 82 produces a real output.

Corresponding to the circular shift sequence 66, an input circular shiftsequencer 84, which can comprise a shift register, holds N samples andcircularly shifts the samples in steps that are decreasing multiples ofR samples (where R=N/OS) at a time. This shift undoes the shiftperformed by 66.

The N-sample output of the circular shift sequence 84, Z′(1:N), isreplicated and concatenated as necessary to form an ^(L)/_(DF) samplesequence in input buffer 86, where DF represents the synthesis windowdecimation factor (and is not to be confused with the analysisfilterbank time domain decimation factor R). As discussed below, theparameter DF is less than or equal to OS when the synthesis windowfunction is based on a decimated version of the analysis function;otherwise DF equals 1. This replication and concatenation step is theinverse operation of the time aliasing step previously described. Asillustrated in FIG. 4, this input buffer is shown as ^(L)/_(DF*N)N-sample segments which have been periodically extended from thecircular shift sequence 84. It is possible for ^(L)/_(DF*N) to be, anon-integer fraction. For large synthesis window decimation factors, DF,^(L)/_(DF*N) may also be less than 1, and in such cases the input buffer86 becomes shorter than N samples and comprises only the central portionof Z′(1:N),

The output of the buffer 86 is connected to a multiplication unit 88.The multiplication unit 88 has another input for a synthesis window 89indicated as W(1:DF:L). The window 89 which is L/DF samples long removesunwanted spectral images. The analysis window has a cutoff frequency ofπ/N and the synthesis window has a cutoff frequency of π/R=OS.π/N . Thelatter may be based on the decimated analysis window by setting DF±OS ifthe “droop” (or attenuation) of the analysis filter at its cutofffrequency divided by DF, i.e. at π/N.DF, is not significant since thisrepresents the attenuation of the synthesis window at π/N. In such acase, the synthesis window function is generated by decimating theanalysis window coefficients by a factor of DF±OS. This constraint (i.e.having the synthesis window based on the analysis window) is preferablefor memory limited applications and may be removed, advantageously, ifsufficient memory is available. As indicated previously, I, correspondsto the number of samples held in the buffer 56 in the analysisfilterbank (FIG. 3), and DF represents the synthesis window decimationfactor, where for DF equal to 2 every other sample is deleted. Similarlyto the analysis window function, the synthesis window function W(1:DF:L)(this notation indicates a vector derived from a vector W by starting atindex 1 and selecting every DF′th sample not exceeding index L) isideally a good M-band filter, i.e. a good low pass filter which haszeros at every interval of N/DF samples. However, as with the analysiswindow, other window functions can also be used. The output of themultiplication unit 88 is connected to a summation unit 90. Thesummation unit 90 has an output unit connected to an output buffer 92.The buffer 92 has an input at one end for additional samples and anadditional sample input 94, so that the output buffer 92 acts like ashift register that shifts R samples each time a new input block isreceived.

The output of the summation unit 90 is supplied to the buffer 92. Asindicated by the arrows, the contents of the buffer 92 are periodicallyshifted to the left by R samples. This is achieved by adding R zeros tothe right hand end of the buffer 92, as viewed. Following this shift,the contents of the buffer 92 are added to the product of W(1:DF:L) andthe periodically extended buffer 86, The result is stored in the buffer92 which holds ^(L)/_(DF) samples (or equivalently ^(L)/_(DF*N) N-samplesegments). As previously explained, the buffer 92 may be less than oneN-sample in length for large synthesis window decimation factors, DF.

It must be appreciated that, the output from the buffer 92, at the lefthand end, is a signal which in effect has been added ^(L)/_((DF*R))times, so as to comprise portions of signals added together.

Because the coefficients of the window function W(1:L), the length ofthe window L, and the synthesis window decimation factor DF are allprogrammable parameters (by way of DSP unit 18), the present inventionallows for a selectable number of channels, and a selectable range ofbandwidths. As an additional advantage, the selectable even/odd stackingfeature permits the bands to be shifted in unison by half of the channelbandwidth, without increasing delay. Thus the present invention allowsthe number of channels or bands and the width of those bands to beselected.

R samples at a time are taken from the buffer 92 and sent to amultiplication unit 96. Mirroring the circular ± sign sequencer input54, there is another circular ± sign sequencer input 98, which again hasa series of multiplication factors of +1 or −1, depending upon whetheran odd or even DFT is executed. This step exactly undoes the modulationstep performed in the analysis stage.

After multiplication in the unit 96 by the appropriate factors, Rsamples are present at the output 100, as indicated as Y(1:R). Thesesamples are fed to the D/A converter 20.

The resynthesis procedure in addition to generating the correct signalin each band, produces unwanted spectral images which, when over-sampledby OS, are spaced OS times farther apart than for critical sampling, Thesynthesis window performed the function of removing these images similarto the function of the analysis window in preventing aliasing. Sincethese window function are related, when memory is scarce, it ispreferable to use a synthesis window related to the analysis window inorder to conserve memory. In general, the reconstruction window callconveniently be the synthesis window decimated by DF, the synthesiswindow decimation factor.

As indicated at 32, connections to a programmable DSP 18 are provided,to enable the DSP to implement a particular processing strategy. Theprogrammable DSP 18 comprises a processor module 34 including a volatilememory 36, The processor 34 is additionally connected to a nonvolatilememory 38 which is provided with a charge pump 40.

As detailed below, various communication ports are provided, namely: a16 bit input/output port 42, a synchronous serial port 44 and aprogramming interface link 46.

The frequency band signals received by the DSP 18 represent thefrequency content of the different bands and are used by the digitalsignal processor 34 to determine gain adjustments, so that a desiredprocessing strategy can be implemented. The gains are computed based onthe characteristics of the frequency band signals and are then suppliedto the multipliers 28. While individual multipliers 28 are shown, inpractice, as already indicated these could be replaced by one or moremultiplier resources shared amongst the filterbank bands. This can beadvantageous, as it reduces the amount of processing required by theDSP, by reducing the gain update rate and by allowing furthercomputations to be done by the more efficient ASIC. In this manner, thememory requirements are also reduced and the DSP unit can remain insleep mode longer.

The processor 34 can be such as to determine when gain adjustments arerequired. When gain adjustments are not required, the whole programmableDSP unit 18 can be switched into a low-power or standby mode, so as toreduce power consumption and hence to extend battery life.

In another variant of the invention, not shown, the multipliers 28 areomitted from the ASIC. The outputs from the analysis filterbank 26 wouldthen be supplied to the digital signal processor 34, which would bothcalculate the gains required and apply them to the signals for thedifferent bands. The thus modified band signals would then be fed backto the ASIC and then to the synthesis filterbank 30. This would beachieved by a shared memory interface, which is described below.

Communication between the ASIC 16 and the programmable DSP 18 ispreferably provided by a shared memory interface. The ASIC 16 and theDSP 18 may simultaneously access the shared memory, with the onlyconstraint being that both devices cannot simultaneously write to thesame location of memory.

Both the ASIC 16 and programmable DSP 18 require non-volatile memory forstorage of filter coefficients, algorithm parameters and programs asindicated at 38. The memory 38 can be either electrically erasableprogrammable read only memory (EEPROM) or Flash memory that can be readfrom or written to by the processor 34 as required. Because it is verydifficult to achieve reliable operation for large banks (e.g., 8 kbyte)of EEPROM or Flash memory at low supply voltages (1 volt), thecharge-pump 40 is provided to increase the non-volatile memory supplyvoltage whenever it is necessary to read from or write to non-volatilememory. Typically, the non-volatile memory 38 and its associated chargepump 40 will be enabled only when the whole apparatus or hearing aid“boots”; after this it will be disabled (powered down) to reduce powerconsumption.

Program and parameter information are transmitted to the digital signalprocessor 34 over the bi-directional programming interface link 46 thatconnects it to a programming interface. It will thus be appreciated thateither the programming interface link 46 or the audio link through themicrophone 10 (and optional second microphone for a stereoimplementation), for the synthesized audio band signal, provide aselection input enabling the number of frequency bands, the width ofeach band, even or odd stacking, and other parameters to be selected.This interface receives programs and parameter information from apersonal computer or dedicated programmer over a bi-directional wired orwireless link. When connected to a wired programming interface, powerfor non-volatile memory is supplied by the-interface; this will furtherincrease the lifetime of the hearing aid battery. As detailed inassignee's copending application No. 09/060,820 filed simultaneouslyherewith, a specially synthesized audio band signal can also be used toprogram the digital filterbank hearing aid.

The synchronous serial port 44 is provided on the DSP unit 18 so that anadditional analog-to-digital converter can be incorporated forprocessing schemes that require two input channels (e.g.,beamforming—beamforming is a technique in the hearing aid art enabling ahearing aid with at least two microphones to focus in on a particularsound source).

The programmable DSP 34 also provides a flexible method for connectingand querying user controls. A 16-bit wide parallel port is provided forthe interconnection of user controls such as switches, volume controls(shaft encoder type) and for future expansion. Having these resourcesunder software control of the DSP unit 18 provides flexibility thatwould not be possible with a hardwired ASIC implementation.

It is essential to ensure the reliability of the digital filterbankhearing aid in difficult operating environments. Thus, error checking orerror checking and correction can be used on data stored in non-volatilememory. Whenever it is powered on, the hearing aid will also perform aself-test of volatile memory and check the signal path by applying adigital input signal and verifying that the expected output signal isgenerated. Finally, a watchdog timer is used to ensure system stability.At a predetermined rate, this timer generates an interrupt that must beserviced or the entire system will be reset. In the event that thesystem must be reset, the digital filterbank hearing aid produces anaudible indication to warn the user.

A number of sub-band coded (i.e., digitally compressed) audio signalscan be stored in the non-volatile memory 38 and transferred to volatilememory (RAM) 36 for real-time playback to the hearing aid user. Thesub-band coding can be as described in chapters 11 and 12 of Jayant, N.S. and Noll, P., Digital Coding of Waveforms (Prentice-Hall; 1984) whichis incorporated herein by this reference. These signals are used toprovide an audible indication of hearing aid operation. Sub-band codingof the audio signals reduces the storage (non-volatile memory) that isrequired and it makes efficient use of the existing synthesis filterbankand programmable DSP because they are used as the sub-band signaldecoder,

Thus, in accordance with the present invention, the digital processingcircuit consists of an analysis filterbank that splits the digitalrepresentation of the input time domain signal into a plurality offrequency bands, a means to communicate this information to/from aprogrammable DSP and a synthesis filterbank that recombines the bands togenerate a time domain digital output signal.

Ideally, a digital hearing aid, or indeed any hearing aid, would havenon-uniform frequency bands that provide high resolution in frequencyonly where it is required. This would minimize the number of bands,while enabling modification of the gain or other parameters only whererequired in the frequency spectrum. However, the most efficientimplementation of multi-channel filters, where the implementation isbased on known transforms such as the Fourier transform, have uniformspacing. This naturally results from the fact that uniform sampling intime maps to uniform spacing in frequency. Thus, the present inventionprovides a multi-channel filter design with uniform spacing.

The number of bands, i.e., frequency resolution, required by a digitalhearing aid depends upon the application. For frequency responseadjustment at low frequencies, a digital hearing aid should be capableof adjustment in 250 Hz frequency steps. This fine adjustment allows thelow-frequency gain targets at audiometric frequencies (the standardfrequencies at which hearing characteristics are measured) to beaccurately set.

The sampling rate used by a digital hearing aid is related to thedesired output bandwidth. Since speech typically has little energy above5 kHz and covering this frequency range results in highly intelligiblespeech, a sampling rate of 16 kHz, corresponding to a bandwidth of 8 kHzwas chosen to allow a margin for safety. At a proportional increase inpower consumption, however, a sampling rate of 24 kHz or beyond mayprove desirable for higher fidelity. The minimum sampling rate requiredto achieve a desired output bandwidth should be selected to minimizepower consumption. Adequate frequency coverage and resolution isachieved by using sixteen 500 Hz wide bands. This in turn requires a32-point discrete Fourier transform. Although the bands are 500 Hz wideinthis typical embodiment, the band edges may be adjusted in unison by250 Hz steps. This is accomplished through the use of the DFT with evenor odd stacking.

Compressor systems, which attempt to map variations in input signallevel to smaller variations in output level, typically employ two ormore bands so that high-level sounds in one band do not reduce the gainin other bands and impair speech perception, There is considerabledebate on the number of bands that should be provided for an idealcompression system, assuming there is some perfect ideal system. Thecurrent consensus seems to be that two bands are better than one, butthat more than two bands does not lead to improved speech receptionthresholds. However, some results and opinions cast doubts on pastresults and methodologies that were used to evaluate multichannelcompression systems.

For noise reductions systems, however, it is desirable to have a largenumber of bands so that only those portions of the spectrum that arenoise can be attenuated, while not affecting parts of the spectrumwithout noise. To extract speech from noise, the filters should havesmall bandwidths to avoid removing speech harmonies. For the 8 kHzbandwidth mentioned, 128 bands provide bandwidths of 62.5 Hz which isadequate to avoid this problem.

There exist many possible tradeoffs between the number of bands, thequality of the bands, filterbank delay and power consumption. Ingeneral, increasing the number or quality of the filterbank bands leadsto increased delay and power usage. For a fixed delay, the number ofbands and quality of bands are inversely related to each other. On onehand, 128 channels would be desirable for flexible frequency adaptationfor products that can tolerate a higher delay. The larger number ofbands is necessary for the best results with noise reduction andfeedback reduction algorithms.

On the other hand, 16 high-quality channels would be more suitable forextreme frequency response manipulation. Although the number of bands isreduced, the interaction between bands can be much lower than in the 128channel design. This feature is necessary in products designed to fitprecipitous hearing losses or other types of hearing losses where thefilterbank gains vary over a wide dynamic range with respect to eachother. Now, in accordance with the present invention, the filterbanks26, 30 provide a number of bands, which is a programmable parameter. Inaccordance with the discussion above, the number of bands is typicallyin the range of 16-128.

A further increase in low-frequency resolution (i.e. more channels) maybe obtained by further processing of one or more analysis filterbankoutput samples. This processing causes additional system delays sincethe additional samples must be acquired first before processing. Thistechnique may be acceptable at low frequencies and for certainapplications.

For applications requiring low processing delay and high frequencies,the converse of this technique is useful. Initial processing is done onfewer bands lowering the processing delay and increasing the bandwidthof the individual filter bands. Subsequent processing is performed on,typically, lower frequency bands to increase the frequency resolution atthe expense of low-frequency delay; i.e. the lower frequency bands arefurther divided, to give narrower bands and greater resolution.

Commonly, there are two basic types of filterbanks, namely finiteimpulse response (FIR) and infinite impulse response (IIR). FIRfilterbanks are usually preferred, because they exhibit betterperformance in fixed-point implementations, are easier to design and ofconstant delay. Frequency bands in a filterbank can be non-overlapping,slightly overlapping or substantially overlapped. For hearing aidapplications, slightly overlapped designs are preferred, because theyretain all frequency domain information while providing lowerinteraction between adjacent bands. Ideally, the bands would be designedto abut precisely against each other with no overlap. This however wouldrequire very large order filters with unacceptably large delay, so inpractice low-order filters (128 to 512 points) are used, which createsslightly overlapped designs.

As discussed previously, uniform spacing of the bands is provided,because they can be implemented using fast frequency-domain transforms,e.g. either a FFT or a discrete cosine transform, which require lesscomputation than time-domain implementations.

Two types of channel stacking arrangements are known for uniformfilterbanks, as shown in FIG. 2. For even stacking (FIG. 2a) the n=0channel is centred at ω=0 and the centres of the bands are at normalizedfrequencies ω_(n)=2nπ/N,n=0, 1, . . . , N−1.

Correspondingly, for an odd stacking arrangement (FIG. 2b), the n=0channel is centred at a ω=π/N and the band frequencies are atω_(n)=2nπ/N+π/N,n=0, 1, . . . , N−1. These even and odd stackingarrangements are shown in FIG. 2a and 2 b respectively. For audioprocessing applications, odd stacking is generally preferred over evenstacking, because it covers the entire input signal bandwidth between DCand the Nyquist frequency equally with no half bands. The frequency band(DC to sampling rate) in FIG. 2a, 2 b is shown normalized to cover aspan of 2π.

The ability to select either even or odd stacking is a considerableadvantage, as it doubles the number of useable band edges. The placementof the band edges is then selectable. The band edges can be selecteddepending on the characteristics of a person's hearing loss. FIG. 2shows, as a dashed line, a typical input spectrum for 0 to π (thenormalized Nyquist frequency) that is asymmetric about f=π because thesignal is sampled at a rate of 2π. FIG. 2c and 2 d also show the odd andeven stacking arrangements. They also show real or characteristic filterresponses to each filter.

While the preferred embodiment of the invention has been described, itwill be appreciated that many variations are possible within the scopeof the invention.

Some types of hearing loss result in precipitous losses or other typesof losses which vary significantly across the frequency spectrum, whichin turn requires the filterbank gains to vary over a wide dynamic rangewith respect to each other. In such a case, it becomes advantageous toprovide some other frequency dependent gain in a fixed filter before theinput to the analysis filterbank 26. This can provide a co-operativearrangement, in which the fixed or prefilter provides a coarseadjustment of the frequency response. This then leaves the analysisfilterbank to provide a fine, dynamic adjustment and the problems ofwidely varying gains between adjacent filter bands are avoided.

The filterbank structure of the present invention provides a naturalstructure for the generation of pure tones at the centre frequencies ofeach filter band. As these tones hit a majority of the audiometricfrequencies that are employed to measure hearing loss, the filterbankcan be programmed to emit pure tones. With these pure tones, the hearingaid can be used directly, to assess hearing loss, replacing theaudiometer currently used and making the test more accurate andrealistic.

In addition to, or instead of, the prefilter mentioned above, there maybe a further requirement for frequency control within a band, whichalternatively could be characterised as splitting a band into a numberof sub bands. To provide this filtering flexibility, and to maintain thebest signal to noise ratio, and to maintain the simple evenly spacedband structure outlined above, a postfilter can be added after thesynthesis filterbank 30.

There can be cases involving the fitting of severe losses requiringsignificant amounts of high frequency gain. In this situation, if thegain is implemented in the filterbanks, the hearing aid can becomeacoustically unstable. Here, the postfilter would act as a notch filter,to remove only the narrow band of oscillatory frequencies, while leavingthe rest of the filter band alone. Alternatively, this can also beaccomplished in the filterbank itself.

We claim:
 1. An oversampled filterbank for filtering an informationsignal, the filterbank having a filterbank structure comprising a filtermeans defining a filter bandwidth, said filter means filtering saidinformation signal and separating said information signal into aplurality of frequency band signals, each representing one of aplurality of uniformly spaced frequency bands within said filterbandwidth, said frequency bands being stacked in one of an even and anodd manner and said frequency bands overlapping, such that the summationof the unmodified frequency band responses of the plurality of saidfrequency bands sums to a function within a predetermined passbandripple over said filter bandwidth, wherein the filter means includes aselection input enabling at least one of the following to be selected:(i) the number of frequency band signals, (ii) the bandwidth of saidfrequency bands, (iii) selection of stacking of said frequency bands inone of an even and an odd manner, (iv) the degree of overlap betweensaid frequency bands; (v) an oversampling factor by which said frequencyband signals are sampled above the theoretical minimum of criticalsampling.
 2. A filterbank as claimed in claim 1, wherein the selectioninput enables at least one of the number of frequency bands and whethersaid frequency bands are stacked in an even or odd manner to beselected, said number of frequency bands being equal to N, and thefilter means comprises: (a) a first analysis filterbank means forseparating said signal into the plurality of N separate frequency bandsignals; (b) processing means for receiving and processing each of saidseparate frequency band signals to provide N separate processedfrequency band signals; and (c) a second synthesis filterbank means forreceiving and recombining the N separate processed frequency bandsignals into a single output signal, wherein both of the first analysisfilterbank means and the second synthesis filterbank means are connectedto the selection input, the processing means being coupled between thefirst analysis filterbank means and the second synthesis filterbankmeans.
 3. A filterbank as claimed in claim 2, which comprises adedicated application specific integrated circuit (ASIC), said ASICincluding the first analysis and the second synthesis filterbanks, and aprogrammable digital signal processor for controlling the number offrequency bands and the bandwidth of each frequency band, said digitalsignal processor being provided with the selection input.
 4. Afilterbank as claimed in claim 3, wherein said processing means includesa multiplier means for multiplying each of the frequency band signals byan adjustable gain to provide the N separate processed frequency bandsignals.
 5. A filterbank as claimed in claim 4, wherein the multipliermeans comprises one or more dedicated multiplier resources incorporatedon the application specific integrated circuit.
 6. A filterbank asclaimed in claim 4, wherein the multiplier means comprises a multiplierresource provided on the programmable digital signal processor.
 7. Afilterbank as claimed in claim 1, wherein the selection input enableswhether said frequency bands are stacked in an even or odd manner to beselected.
 8. A filterbank as claimed in claim 1, wherein the selectioninput enables whether said frequency bands abut, overlap, or are spacedapart from one another to be selected.
 9. A filterbank as claimed inclaim 1, wherein the selection input enables the decimation factor to beselected.
 10. A filterbank as claimed in claim 1, wherein the selectioninput enables the degree of overlap in the frequency bands to beselected, including selection of abutting and spaced apart frequencybands.
 11. A filterbank as claimed in claim 1, which includes a sharedmemory interface, for interfacing with a programmable digital signalprocessor.
 12. A filterbank as claimed in claim 1, which includes lowfrequency processing means for additional processing of low-frequencybands to provide additional resolution.
 13. A filterbank as claimed inclaim 2, which includes a prefiltering means connected to the firstanalysis filterbank means, for modifying the gain of at least oneselected portion of the frequency spectrum of said information signal.14. A filterbank as claimed in claim 2 or 13, which includes apostfiltering means connected to the second filterbank means, forpostfiltering the single output signal.
 15. A filterbank as claimed inclaim 3, wherein the first analysis filterbank means, the processingmeans and the second synthesis filterbank means utilize digital signalprocessing, the first analysis filterbank means being adapted to receivean input digital sample stream and the second synthesis filterbank meansproviding an output digital data stream as the output signal wherein thefilterbank includes an analog-to-digital conversion means connected tosaid first analysis filterbank for receiving an original analog signaland for converting said analog signal into an input digital samplestream at an initial input sampling rate which forms said informationsignal for the analysis filterbank, and a digital-to-analog conversionmeans connected to said second synthesis filterbank for converting theoutput digital data stream to form an analog version of said singleoutput signal.
 16. A filterbank as claimed in claim 15, wherein thefirst analysis filterbank means comprises: (a) a blocking means forreceiving the input digital sample stream and blocking a first number, Rwhere R≦N, of the digital samples so as to provide a blocked inputdigital sample stream, the ratio of N/R corresponding to an oversamplingfactor; (b) an analysis window means for applying an analysis windowfunction to the input digital sample stream to provide a windowedblocked digital sample stream, said analysis window function beingdefined by a set of analysis window coefficients; (c) a time foldingmeans for overlapping and adding blocks of said windowed blocked digitalsample stream, each of said blocks comprising N digital samples, toprovide a summed block of N digital samples; and (d) a discretetransform means for receiving said summed block of N digital samples andtransforming the signal into a discrete frequency domain signal having Ncomponents, the N components corresponding to the N frequency bandsignals.
 17. A filterbank as claimed in claim 16, wherein the secondsynthesis filterbank means comprises: (a) an inverse discrete transformmeans for receiving said N processed frequency band signals and foreffecting an inverse transform to form a block of N digital samples; (b)a replication and concatenation means for replicating and concatenatingsaid processed block of N digital samples to provide a periodicallyextended block of N digital samples; (c) a synthesis window means forapplying a synthesis window function to said extended block of N digitalsamples to provide a windowed periodically extended block of N digitalsamples, said synthesis window function being defined by a set ofsynthesis window coefficients; and (d) a summation buffer means forreceiving said windowed periodically extended block of N digital samplesand adding said windowed periodically extended samples to the shiftedcontents of the buffer each time a new windowed periodically extendedsample is received, so as to provide a processed information signal. 18.A filterbank as claimed in claim 17, wherein said synthesis windowfunction is based on a decimated version of said analysis windowfunction.
 19. A filterbank as claimed in claim 16, 17, or 18 in whichthe programmable digital signal processor is operable to vary saidanalysis window coefficients and said synthesis window coefficients. 20.A filterbank as claimed in claim 16 or 17, in which the programmabledigital signal processor is operable to vary said oversampling factor,and in which the oversampling factor is at least equal to
 2. 21. Afilterbank as claimed in claim 3 in which the programmable digitalsignal processor is operable to provide either even stacking or oddstacking of the frequency bands within said filter bandwidth.
 22. Afilterbank as claimed in claim 1, 2, or 3, in which said filterbank isincorporated in a digital hearing aid.
 23. A filterbank as claimed inclaim 1, wherein the selection input enables the number of frequencyband signals to be selected.
 24. A filterbank as claimed in claim 23,wherein the selection input further enables the bandwidth of saidfrequency bands to be selected.
 25. An oversampled filterbank, forfiltering an information signal, the filterbank having a filterbankstructure comprising: (a) a first analysis filterbank means forseparating said signal into a plurality of N separate frequency bands,wherein the first analysis filterbank means includes transform means fortransforming the audio signal into the frequency domain, with the Nseparate frequency band signals being present in the frequency domain;(b) processing means for receiving and processing each of said separatefrequency band signals to provide N separate processed frequency bandsignals, wherein said processing means includes a multiplier means formultiplying each of the frequency band signals by an adjustable gain toprovide the N separate processed frequency band signals; (c) a secondsynthesis filterbank means for receiving and recombining the N separateprocessed frequency band signals into a single output signal, theprocessing means being coupled between the first analysis filterbankmeans and the second synthesis filterbank means, wherein the secondsynthesis filterbank means includes inverse transform means fortransforming the N separate frequency band signals into the singleoutput signal in the time domain; (d) a selection input connected toboth of the first analysis filterbank means and the second synthesisfilterbank means, to enable the number of bands and the bandwidth ofeach frequency band to be selected, wherein the selection input furtherenables at least one of the following to be selected: (i) the number offrequency band signals; (ii) the bandwidth of said frequency bands;(iii) selection of stacking of said frequency bands in one of an evenand an odd manner; (iv) the degree of overlap between said frequencybands; (v) an oversampling factor by which said frequency band issampled above the theoretical minimum of critical sampling wherein thefilterbank comprises an application specific integrated circuit, saidapplication specific integrated circuit including the first analysis andthe second synthesis filterbanks, and a programable digital signalprocessor for controlling the number of frequency bands and thebandwidth of each frequency band, said digital signal processor beingprovided with the selection input.
 26. A filterbank as claimed in claim25, which is adapted to receive a single real monaural informationsignal, wherein said transform means generates non-negative frequencyband signals and negative frequency band signals, said negativefrequency band signals being derivable from the non-negative frequencyband signals, and said processing means processes only said non-negativefrequency band signals.
 27. A filterbank as claimed in claim 25, whereinthe filterbank is adapted to filter an audio signal comprising first andsecond real monaural information signals which are combined into acomplex stereo signal and wherein said transform means generates Ncombined frequency band signals, and wherein said processing meansincludes: (a) channel separation means for separating the N combinedfrequency band signals into the N frequency band signals correspondingto said first information signal and the N frequency band signalscorresponding to said second information signal, each of said Nfrequency band signals comprising non-negative and negative frequencyband signals; (b) first independent channel processing means connectedto the channel separation means for receiving and processing each ofsaid separate frequency band signals of said first information signal toprovide a first set of N separate processed frequency band signals; (c)second independent channel processing means connected to channelseparation means for receiving and processing each of said separatefrequency band signals of said second information signal to provide asecond set of N separate processed frequency band signals; and (d)channel combination means connected to the first and second independentchannel processing means for combining said first set of N processedseparate frequency band signals and said second set of N processedseparate frequency band signals.
 28. A filterbank as claimed in claim27, wherein said first and second independent channel processing meanseach process only the non-negative frequency band signals of thecorresponding information signal, the negative frequency band signalsbeing derivable from the non-negative frequency band signals.
 29. Amethod of processing an information signal to selectively modifydifferent frequency bands, the method comprising the steps of: (1)defining a filter frequency bandwidth to be analyzed; (2) dividing thefilter frequency bandwidth into a plurality of uniformly spaced bandsand defining characteristics of the filter bands, and selecting stackingof said frequency bands into one of an even and an odd manner and thedegree of overlap between said frequency bands; (3) filtering theinformation signal to separate the signal into a plurality of frequencyband signals, each representing one of said uniform filter bands,including oversampling the frequency band signals by a fraction above atheoretical initial sampling, thereby determining a decimation factor;(4) processing the frequency band signals; and (5) recombining thesignals of the individual bands to form an output signal; wherein themethod includes as an additional step (6), at least one of: (i)selecting the number of frequency band signals, (ii) selecting thebandwidth of said frequency bands, (iii) selecting stacking of saidfrequency bands in one of an even and an odd manner, (iv) selecting thedegree of overlap of said frequency bands, and (v) selecting theoversampling a decimation factor by which said frequency band signalsare sampled above critical sampling.
 30. A method as claimed in claim29, which includes selecting the degree of overlap of said frequencybands and providing for the selection of abutting and spaced apartfrequency bands.
 31. A method as claimed in claim 29, wherein the inputin step (6) enables whether said frequency bands abut, overlap, or arespaced apart from one another to be selected.
 32. A method as claimed inclaim 29, wherein the input in step (6) enables the decimation factor tobe selected.
 33. A method as claimed in claim 29, wherein the input instep (6) enables whether said frequency bands are stacked in an even orodd manner to be selected.
 34. A method as claimed in claim 29, whereinstep (4) comprises setting a gain for each frequency band andmultiplying each frequency band signal by the respective set gain.
 35. Amethod as claimed in claim 29 which comprises applying the method to anaudio information signal in a digital hearing aid.
 36. A method asclaimed in claim 35, including enhancing low-frequency bands byadditional processing.
 37. A method as claimed in claim 36, whichincludes subdividing at least one low-frequency band into smaller bandsfor individual processing.
 38. A method as claimed in claim 35, whichcomprises selecting the number of bands and the width of the bands, independence upon acceptable delays and desired resolution.
 39. A methodas claimed in claim 29, wherein the input in step (6) enables the numberof frequency band signals to be selected.
 40. A method as claimed inclaim 39, wherein the input in step (6) further enables the bandwidth ofsaid frequency bands to be selected.
 41. A method as claimed in claim29, the method further comprising: (a) in step (3) separating saidinformation signal into N separate frequency band signals; (b) in step(4) processing each of said separate frequency band signals to provide Nseparate processed frequency band signals; (c) in step (5), recombiningthe N separate processed frequency band signals to form the outputsignal; and (d) selecting either the number of frequency bands orwhether said frequency bands are stacked in an even or odd manner.
 42. Amethod as claimed in claim 41, which includes transforming theinformation signal into the frequency domain, providing N separatefrequency band signals in the frequency domain, and effecting an inversetransform of the N separate processed frequency band signals into theoutput signal in the time domain.
 43. A method as claimed in claim 42,which comprises generating non-negative frequency band signals andnegative frequency band signals, the negative frequency band signalsbeing derivable from the non-negative frequency band signals, and, instep (4), processing only said non-negative frequency band signals. 44.A method as claimed in claim 43, which comprises: (a) receiving aninformation signal comprising first and second real monaural informationsignals combined into a complex stereo signal and, when transforming theinformation signal into the frequency domain, generating N combinedfrequency band signals; (b) separating the N combined frequency bandsignals into the N frequency band signals corresponding to said firstinformation signal and the frequency band signals corresponding to saidsecond information signal, each of said N frequency band signalscomprising non-negative and negative frequency band signals; (c)processing each of said separate frequency band signals of said firstinformation signal to provide a first set of N separate processedfrequency band signals; (d) processing each of said separate frequencyband signals of said second information signal to provide a second setof N separate processed frequency band signals; and (e) combining saidfirst set of N processed separate frequency band signals and said secondset of N processed separate frequency band signals.
 45. A method asclaimed in claim 44, which comprises, for each of said first and secondinformation signals processing only the non-negative frequency bandsignals of the corresponding information signal.
 46. A method as claimedin claim 42, wherein the method is effected by digital signalprocessing, the method including: passing an original analog signalthrough an analog-to-digital conversion means to convert the analogsignal into an input digital sample stream at an initial input samplingrate which forms said information signal, and wherein the output signalafter the inverse transform comprises an output digital data stream; andeffecting a digital to analog conversion of the output digital datastream to form an analog version of the output signal.
 47. A method asclaimed in claim 46, wherein the step of transforming the informationsignal into the frequency domain comprises: (a) blocking the inputdigital sample stream into blocks of R samples, where R≦N, to provide ablocked input digital sample stream, the ratio of N/R corresponding toan oversampling factor; (b) applying an analysis window function to theinput digital sample stream to provide a windowed blocked digital samplestream, said analysis window function being defined by a set of analysiswindow coefficients; (c) overlapping and adding blocks of said windowedblocked digital sample stream, each of said blocks comprising N digitalsamples, to provide a summed block of N digital samples; and (d)transforming the signal into a discrete frequency domain signal having Ncomponents, the N components corresponding to the N frequency bandsignals.
 48. A method as claimed in claim 47, wherein the step ofeffecting an inverse transform of the N separate processed frequencyband signals comprises: (a) effecting an inverse transform to form ablock of N digital samples; (b) replicating and concatenating saidprocessed block of N digital samples to provide a periodically extendedblock of N digital samples; (c) applying a synthesis window function tosaid extended block of N digital samples to provide a windowedperiodically extended block of N digital samples, said synthesis windowfunction being defined by a set of synthesis window coefficients; (d)adding said windowed periodically extended block of N samples to asummation buffer; and (e) each time a new windowed periodically extendedsample is received, shifting the contents of the summation buffer by Rsamples from one end of the summation buffer towards the other end ofthe buffer, providing zeros to fill the R empty samples at the one endof the buffer, and passing the R samples displaced out of the other endof the buffer to an output to provide a processed information signal.49. A method as claimed in claim 48 wherein the analysis windowcoefficients and the synthesis window coefficients can be varied.
 50. Amethod as claimed in claim 48, which includes forming the synthesiswindow function by decimating the analysis window function.
 51. A methodas claimed in claims 42, 46 or 48, which includes selecting stacking ofthe frequency bands in one of even stacking and odd stacking, within thefrequency bandwidth.
 52. A method as claimed in claim 47 or 48 whereinthe oversampling factor can be varied and is at least equal to 2.